sensobol: an R package to compute variance-based sensitivity indices

Arnald Puy*, Andrea Saltelli, Samuele Lo Piano, Simon A. Levin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
49 Downloads (Pure)

Abstract

The R package sensobol provides several functions to conduct variance-based uncertainty and sensitivity analysis, from the estimation of sensitivity indices to the visual representation of the results. It implements several state-of-the-art first and total-order estimators and allows the computation of up to fourth-order effects, as well as of the approximation error, in a swift and user-friendly way. Its flexibility makes it also appropriate for models with either a scalar or a multivariate output. We illustrate its functionality by conducting a variance-based sensitivity analysis of three classic models: the Sobol’ (1998) G function, the logistic population growth model of Verhulst (1845), and the spruce bud-worm and forest model of Ludwig, Jones, and Holling (1976).

Original languageEnglish
Pages (from-to)1-37
Number of pages37
JournalJournal of Statistical Software
Volume102
Issue number5
DOIs
Publication statusPublished - 30 Apr 2022

Bibliographical note

Funding Information:
This work has been funded by the European Commission (Marie Skłodowska-Curie Global Fellowship, grant number 792178 to AP).

Publisher Copyright:
© 2022, American Statistical Association. All rights reserved.

Keywords

  • uncertainty
  • sensitivity
  • modeling
  • ecology

ASJC Scopus subject areas

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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